# Agent Runtime Module Testing Plan

## 🎯 Testing Goals

- Ensure functional correctness of the reimplemented Runtime module
- Verify performance and stability of the Starlette-based server
- Test Pydantic data model validation and serialization
- Verify correctness of asynchronous operations and streaming responses
- Ensure complete compliance with design documentation
- Test decorator API usability and correctness

## 📁 Test Directory Structure

```
tests/
├── agent_runtime/
│   ├── __init__.py
│   ├── conftest.py                    # Shared test configuration and fixtures
│   ├── runtime/                       # Runtime module tests
│   │   ├── __init__.py
│   │   ├── unit/                      # Unit tests
│   │   │   ├── test_models.py         # Data model tests
│   │   │   ├── test_context.py        # Context management tests
│   │   │   ├── test_server.py         # HTTP server tests
│   │   │   ├── test_app.py            # AgentRuntimeApp tests
│   │   │   └── test_decorators.py     # Decorator functionality tests
│   │   ├── integration/               # Integration tests
│   │   │   ├── test_end_to_end.py     # End-to-end Agent runtime tests
│   │   │   ├── test_server_app.py     # Server and application integration tests
│   │   │   ├── test_streaming.py      # Streaming response integration tests
│   │   │   ├── test_middleware.py     # Middleware integration tests
│   │   │   └── test_error_handling.py # Error handling integration tests
│   │   ├── performance/               # Performance tests
│   │   │   ├── test_load.py           # Load tests
│   │   │   ├── test_concurrent.py     # Concurrent tests
│   │   │   ├── test_memory.py         # Memory usage tests
│   │   │   └── test_latency.py        # Latency tests
│   │   ├── compatibility/             # Compatibility tests
│   │   │   ├── test_api_compatibility.py  # API compatibility tests
│   │   │   └── test_legacy_support.py     # Backward compatibility tests
│   │   └── mocks/                     # Mocks and test utilities
│   │       ├── __init__.py
│   │       ├── mock_agent.py          # Mock Agent functions
│   │       ├── mock_server.py         # Mock server
│   │       └── test_fixtures.py       # Test data and fixtures
│   ├── examples/                      # Example tests
│   │   ├── test_basic_agent.py        # Basic Agent example tests
│   │   └── test_streaming_agent.py    # Streaming Agent example tests
│   └── AGENT_RUNTIME_CLIENT_TESTING_PLAN.md  # Existing Client testing plan
```

## 🧪 Unit Testing Plan

### 1. Data Model Tests (`test_models.py`)

**Test Scope:**
- Pydantic model validation and serialization
- Kubernetes-style AgentConfig
- Enum types and constants
- Backward compatibility properties

**Test Cases:**

#### AgentConfig Related
- ✅ AgentConfig complete configuration validation
- ✅ AgentMetadata required field validation
- ✅ RuntimeSpec resource limit validation
- ✅ SandboxSpec template ID validation
- ✅ AgentStatus phase enum
- ✅ Configuration serialization/deserialization
- ❌ Invalid email format rejection
- ❌ Invalid file extension rejection
- ❌ Out-of-range resource limit rejection

#### RuntimeConfig Related
- ✅ Default configuration value correctness
- ✅ Port range validation
- ✅ CORS configuration correctness
- ❌ Invalid port number rejection
- ❌ Invalid host address rejection

#### Request/Response Models
- ✅ InvocationRequest creation and validation
- ✅ InvocationResponse structure correctness
- ✅ PingResponse status enum
- ✅ Backward compatible properties (session_id)
- ❌ Invalid request data rejection

### 2. Context Management Tests (`test_context.py`)

**Test Scope:**
- RequestContext model functionality
- AgentRuntimeContext context management
- Thread safety
- Backward compatibility

**Test Cases:**
- ✅ RequestContext creation and property access
- ✅ Backward compatible session_id property
- ✅ AgentRuntimeContext set/get
- ✅ Context clearing functionality
- ✅ Context isolation in multi-threaded environments
- ✅ Correct ContextVar usage
- ❌ Invalid context data handling

### 3. HTTP Server Tests (`test_server.py`)

**Test Scope:**
- AgentRuntimeServer initialization
- Starlette application configuration
- Route handling
- Middleware support

**Test Cases:**

#### Server Initialization
- ✅ Server initialized correctly
- ✅ Configuration parameters applied
- ✅ Starlette application created
- ✅ CORS middleware configured
- ✅ Route registration correctness

#### Endpoint Handling
- ✅ Root endpoint (/) response
- ✅ Health check endpoint (/ping)
- ✅ Invocation endpoint (/invocations)
- ✅ OPTIONS request handling
- ❌ Non-existent endpoint returns 404

#### Request Processing
- ✅ JSON request parsing
- ✅ Request size limiting
- ✅ Request header handling
- ✅ Context creation and setting
- ❌ Invalid JSON format rejection
- ❌ Oversized request rejection

#### Agent Function Execution
- ✅ Synchronous function execution
- ✅ Asynchronous function execution
- ✅ Function signature auto-detection
- ✅ Parameter passing correctness
- ❌ Function execution exception handling

#### Streaming Response
- ✅ Synchronous generator handling
- ✅ Asynchronous generator handling
- ✅ Regular iterator handling
- ✅ Streaming data format
- ❌ Streaming response exception handling

### 4. AgentRuntimeApp Tests (`test_app.py`)

**Test Scope:**
- Application initialization and configuration
- Decorator functionality
- Server start and stop
- Property access

**Test Cases:**

#### Application Initialization
- ✅ Default configuration initialization
- ✅ Custom configuration initialization
- ✅ Debug mode enabled
- ✅ Configuration parameter override

#### Decorator Functionality
- ✅ @entrypoint decorator registration
- ✅ @ping decorator registration
- ✅ @middleware decorator registration
- ✅ Multiple decorators coexist
- ❌ Duplicate registration handling

#### Runtime Control
- ✅ Server startup process
- ✅ Port and host configuration
- ✅ Entrypoint function validation
- ❌ Unregistered entrypoint error

#### Context Access
- ✅ context property access
- ✅ Context state correctness

### 5. Decorator Functionality Tests (`test_decorators.py`)

**Test Scope:**
- Decorator syntax sugar
- Function type detection
- Parameter passing
- Return value handling

**Test Cases:**

#### entrypoint Decorator
- ✅ Synchronous function decoration
- ✅ Asynchronous function decoration
- ✅ Single-parameter function (request only)
- ✅ Two-parameter function (request + context)
- ✅ Generator function decoration
- ✅ Asynchronous generator function decoration
- ✅ Return value unchanged

#### ping Decorator
- ✅ Synchronous health check function
- ✅ Asynchronous health check function
- ✅ Return dictionary format
- ✅ Return PingResponse object
- ✅ Custom health check logic

#### middleware Decorator
- ✅ Middleware function registration
- ✅ Execution order correctness
- ✅ Request/response processing
- ✅ Exception propagation

## 🔗 Integration Testing Plan

### 1. End-to-End Tests (`test_end_to_end.py`)

**Test Scenarios:**
- Complete Agent application runtime workflow
- Real HTTP requests/responses
- Multiple invocation method validation

**Test Flow:**
1. Create AgentRuntimeApp
2. Register Agent function
3. Start server
4. Send HTTP request
5. Validate response format
6. Close server

**Test Cases:**
- ✅ Basic Agent invocation complete workflow
- ✅ Agent invocation with parameters
- ✅ Custom health check workflow
- ✅ Asynchronous Agent invocation workflow
- ✅ Error response format validation

### 2. Server Application Integration Tests (`test_server_app.py`)

**Test Scenarios:**
- AgentRuntimeApp and AgentRuntimeServer integration
- Configuration passing and application
- Lifecycle management

**Test Cases:**
- ✅ Application configuration correctly passed to server
- ✅ Decorator-registered functions called correctly
- ✅ Middleware chain executed correctly
- ✅ Server startup state synchronized

### 3. Streaming Response Integration Tests (`test_streaming.py`)

**Test Scenarios:**
- End-to-end streaming response
- Different types of generator handling
- Streaming data integrity

**Test Cases:**
- ✅ Synchronous generator end-to-end streaming response
- ✅ Asynchronous generator end-to-end streaming response
- ✅ Large data streaming transfer
- ✅ Streaming response interruption handling
- ✅ Client streaming data reception

### 4. Middleware Integration Tests (`test_middleware.py`)

**Test Scenarios:**
- Collaborative work of multiple middleware
- Middleware execution order
- Exception propagation in middleware chain

**Test Cases:**
- ✅ Multiple middleware execute in order
- ✅ Middleware modify request/response
- ✅ Middleware exception handling
- ✅ Middleware interact with Agent function

### 5. Error Handling Integration Tests (`test_error_handling.py`)

**Test Scenarios:**
- Error handling at all levels
- Error response format standardization
- Exception propagation and conversion

**Test Cases:**
- ✅ Agent function exception handling
- ✅ Server layer exception handling
- ✅ Middleware exception handling
- ✅ Network layer exception handling
- ✅ Standardized error response format

## 🚀 Performance Testing Plan

### 1. Load Tests (`test_load.py`)

**Test Scenarios:**
- High concurrency request processing
- Long-term runtime stability
- Resource usage monitoring

**Test Metrics:**
- Requests Per Second (RPS)
- Average response time
- 99th percentile response time
- Error rate

**Test Cases:**
- ✅ 100 concurrent user load test
- ✅ 1000 concurrent user load test
- ✅ Long-term runtime stability test
- ✅ Gradual load increase test

### 2. Concurrent Tests (`test_concurrent.py`)

**Test Scenarios:**
- Concurrent request processing correctness
- Context isolation validation
- Thread safety

**Test Cases:**
- ✅ Multi-threaded concurrent invocation
- ✅ Context data isolation
- ✅ Shared resource access safety
- ✅ Race condition detection

### 3. Memory Usage Tests (`test_memory.py`)

**Test Scenarios:**
- Memory leak detection
- Resource cleanup validation
- Large data processing memory management

**Test Cases:**
- ✅ Long-term runtime memory stability
- ✅ Large request processing memory usage
- ✅ Streaming response memory management
- ✅ Garbage collection effectiveness

### 4. Latency Tests (`test_latency.py`)

**Test Scenarios:**
- Request processing latency analysis
- Latency variation under different loads
- Latency distribution statistics

**Test Cases:**
- ✅ Low load latency baseline
- ✅ High load latency variation
- ✅ Latency distribution analysis
- ✅ Tail latency monitoring

## 🔄 Compatibility Testing Plan

### 1. API Compatibility Tests (`test_api_compatibility.py`)

**Test Scenarios:**
- Compliance with design documentation API
- Different Python version compatibility
- Dependency library version compatibility

**Test Cases:**
- ✅ Complete compliance with design documentation API
- ✅ Python 3.9+ compatibility
- ✅ Pydantic 2.x compatibility
- ✅ Starlette latest version compatibility

### 2. Backward Compatibility Tests (`test_legacy_support.py`)

**Test Scenarios:**
- Support for old version API
- Migration path validation
- Deprecation warnings

**Test Cases:**
- ✅ session_id property backward compatibility
- ✅ Old configuration format support
- ✅ Migration warnings displayed correctly

## 🎭 Mocks and Test Utilities

### 1. Mock Agent (`mock_agent.py`)

Provides various types of Mock Agent functions:
- Synchronous/asynchronous Agent functions
- Streaming response Agent functions
- Exception-throwing Agent functions
- Functions with different parameter signatures

### 2. Mock Server (`mock_server.py`)

Simulates external dependencies:
- HTTP client simulation
- Network error simulation
- Timeout simulation

### 3. Test Data (`test_fixtures.py`)

Provides standardized test data:
- Sample configuration data
- Sample request/response data
- Error scenario data
- Performance test data

## 📋 Test Configuration and Utilities

### 1. Shared Configuration (`conftest.py`)

```python
# Main Fixtures
@pytest.fixture
def runtime_config():
    """Provide runtime configuration for testing"""

@pytest.fixture
def agent_config():
    """Provide Agent configuration for testing"""

@pytest.fixture
async def mock_app():
    """Provide Mock AgentRuntimeApp"""

@pytest.fixture
async def test_server():
    """Provide test server instance"""

@pytest.fixture
def sample_agent_function():
    """Provide sample Agent function"""

@pytest.fixture
def mock_request_context():
    """Provide Mock request context"""
```

### 2. Test Markers

```python
# Unit tests
@pytest.mark.unit

# Integration tests
@pytest.mark.integration

# Performance tests
@pytest.mark.performance

# Tests requiring network
@pytest.mark.network

# Slow tests
@pytest.mark.slow

# Compatibility tests
@pytest.mark.compatibility
```

## 🔧 Test Execution Strategy

### 1. Layered Test Execution

```bash
# Unit tests only (fast)
pytest tests/agent_runtime/runtime/unit/ -m unit

# Integration tests
pytest tests/agent_runtime/runtime/integration/ -m integration

# Performance tests (time-consuming)
pytest tests/agent_runtime/runtime/performance/ -m performance

# Compatibility tests
pytest tests/agent_runtime/runtime/compatibility/ -m compatibility

# Complete test suite
pytest tests/agent_runtime/runtime/
```

### 2. Environment Requirements

- **Unit Tests**: No external dependencies, pure Mocks
- **Integration Tests**: Requires starting real server
- **Performance Tests**: Requires sufficient computing resources
- **Compatibility Tests**: Requires multiple Python version environments

### 3. CI/CD Integration

- **Pull Request**: Run unit tests + basic integration tests
- **Main Branch**: Run complete test suite (excluding performance tests)
- **Pre-release**: Run all tests including performance tests

## 📊 Test Coverage Goals

- **Unit Test Coverage**: ≥ 95%
- **Integration Test Coverage**: ≥ 85%
- **Branch Coverage**: ≥ 90%
- **Critical Path Coverage**: 100%

## 🛠️ Required Dependencies

```toml
[tool.poetry.group.test.dependencies]
# Testing framework
pytest = "^7.0.0"
pytest-asyncio = "^0.23.0"
pytest-mock = "^3.12.0"
pytest-cov = "^4.1.0"
pytest-xdist = "^3.3.0"

# HTTP testing
httpx = "^0.27.0"
aioresponses = "^0.7.4"
starlette = "^0.46.2"

# Performance testing
pytest-benchmark = "^4.0.0"
locust = "^2.17.0"
memory-profiler = "^0.61.0"

# Mocks and utilities
responses = "^0.24.0"
freezegun = "^1.2.0"
```

## 📈 Test Execution Plan

### Phase 1: Data Models and Basic Components (Week 1)
1. `test_models.py` - Pydantic model validation
2. `test_context.py` - Context management functionality
3. `test_decorators.py` - Decorator functionality

### Phase 2: Server and Application Components (Week 2)
1. `test_server.py` - HTTP server functionality
2. `test_app.py` - Application class functionality
3. Mock tool development

### Phase 3: Integration Tests (Week 3)
1. `test_end_to_end.py` - End-to-end workflow
2. `test_server_app.py` - Server application integration
3. `test_streaming.py` - Streaming response
4. `test_middleware.py` - Middleware integration
5. `test_error_handling.py` - Error handling

### Phase 4: Performance and Compatibility Tests (Week 4)
1. `test_load.py` - Load testing
2. `test_concurrent.py` - Concurrent testing
3. `test_memory.py` - Memory testing
4. `test_latency.py` - Latency testing
5. `test_api_compatibility.py` - API compatibility
6. `test_legacy_support.py` - Backward compatibility

## 🎯 Quality Assurance

### Code Coverage Requirements
- Each module must have corresponding unit tests
- Critical business logic must achieve 100% coverage
- Exception handling paths must all be tested
- Boundary conditions must be thoroughly tested

### Test Data Management
- Use standardized test data sets
- Mock data consistent with real scenarios
- Test data version control
- Sensitive configuration uses environment variables

### Test Isolation
- Each test case independent of others
- No dependency on external state or other test results
- Appropriate setup and teardown
- Parallel test compatibility

## 📝 Test Reports

### Automated Reports
- Test result statistics and trends
- Code coverage reports and changes
- Performance benchmark comparison and regression detection
- Failed case details and root cause analysis

### Quality Metrics
- Test pass rate ≥ 99%
- Code coverage compliance
- Performance metrics compliance
- Compatibility support status

---

This testing plan ensures the quality and reliability of the reimplemented Agent Runtime module, covering a complete testing system from unit tests to performance tests, and maintaining full compliance with the design documentation.
